Soumick Chatterjee
Orcid: 0000-0001-7594-1188
According to our database1,
Soumick Chatterjee
authored at least 28 papers
between 2019 and 2024.
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Bibliography
2024
Exploration of Interpretability Techniques for Deep COVID-19 Classification Using Chest X-ray Images.
J. Imaging, February, 2024
2023
Sinogram upsampling using Primal-Dual UNet for undersampled CT and radial MRI reconstruction.
Neural Networks, September, 2023
MICDIR: Multi-scale inverse-consistent deformable image registration using UNetMSS with self-constructing graph latent.
Comput. Medical Imaging Graph., September, 2023
Liver segmentation using Turbolift learning for CT and cone-beam C-arm perfusion imaging.
Comput. Biol. Medicine, March, 2023
PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation.
CoRR, 2023
Voxel-wise classification for porosity investigation of additive manufactured parts with 3D unsupervised and (deeply) supervised neural networks.
CoRR, 2023
Flavours of Convolution for Unsupervised Aspect Extraction and Aspect-based Sentiment Analysis.
Proceedings of the Seventh Workshop on Natural Language for Artificial Intelligence (NL4AI 2023) co-located with 22th International Conference of the Italian Association for Artificial Intelligence (AIxIA 2023), 2023
Proceedings of the 4th Italian Workshop on Explainable Artificial Intelligence co-located with 22nd International Conference of the Italian Association for Artificial Intelligence(AIxIA 2023), 2023
2022
DS6, Deformation-Aware Semi-Supervised Learning: Application to Small Vessel Segmentation with Noisy Training Data.
J. Imaging, 2022
Automated SSIM Regression for Detection and Quantification of Motion Artefacts in Brain MR Images.
CoRR, 2022
Weakly-supervised segmentation using inherently-explainable classification models and their application to brain tumour classification.
CoRR, 2022
Primal-Dual UNet for Sparse View Cone Beam Computed Tomography Volume Reconstruction.
CoRR, 2022
DDoS-UNet: Incorporating temporal information using Dynamic Dual-channel UNet for enhancing super-resolution of dynamic MRI.
CoRR, 2022
StRegA: Unsupervised anomaly detection in brain MRIs using a compact context-encoding variational autoencoder.
Comput. Biol. Medicine, 2022
ReconResNet: Regularised residual learning for MR image reconstruction of Undersampled Cartesian and Radial data.
Comput. Biol. Medicine, 2022
Complex Network for Complex Problems: A comparative study of CNN and Complex-valued CNN.
Proceedings of the 5th IEEE International Conference on Image Processing Applications and Systems, 2022
Liver Segmentation in Time-resolved C-arm CT Volumes Reconstructed from Dynamic Perfusion Scans using Time Separation Technique.
Proceedings of the 5th IEEE International Conference on Image Processing Applications and Systems, 2022
2021
Medical Image Anal., 2021
TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models.
CoRR, 2021
CoRR, 2021
Fine-tuning deep learning model parameters for improved super-resolution of dynamic MRI with prior-knowledge.
Artif. Intell. Medicine, 2021
Upgraded W-Net with Attention Gates and Its Application in Unsupervised 3D Liver Segmentation.
Proceedings of the 10th International Conference on Pattern Recognition Applications and Methods, 2021
Proceedings of the 29th European Signal Processing Conference, 2021
2020
CoRR, 2020
DS6: Deformation-aware learning for small vessel segmentation with small, imperfectly labeled dataset.
CoRR, 2020
Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray Images.
CoRR, 2020
2019
Machine learning approach for segmenting glands in colon histology images using local intensity and texture features.
CoRR, 2019
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019